Analysis of possibly misidentified focal calls
Ariana Strandburg-Peshkin
11/10/2020
Explanation
This analysis explores the agreement of two labelers on whether calls both identified as focal on two recordings are the same/different and on who the focal caller was. For now, it uses the output from identify_possible_misidentified_focal_calls.R which was run independently by both Vlad (labeler 1) and Baptiste (labeler 2) to visually inspect and hear calls that were identified on two collar recordings as being “focal” and overlapped in time (see identify_possible_misidentified_focal_calls.R for further info). Here we will take a look at the output to assess the level of agreement between the two labelers, as well as how many “matches” were found and how these things are distributed across call types.
## Loading required package: spam## Loading required package: dotCall64## Loading required package: grid## Spam version 2.5-1 (2019-12-12) is loaded.
## Type 'help( Spam)' or 'demo( spam)' for a short introduction
## and overview of this package.
## Help for individual functions is also obtained by adding the
## suffix '.spam' to the function name, e.g. 'help( chol.spam)'.##
## Attaching package: 'spam'## The following objects are masked from 'package:base':
##
## backsolve, forwardsolve## Loading required package: maps## See https://github.com/NCAR/Fields for
## an extensive vignette, other supplements and source code## Loading required package: viridisLiteNote about the input data
Note that due to some slight differences in which version of the call labels were used, a few calls are not the same between the labels generated by Vlad and those later generated by Baptiste. In more detail, there were 2942 matches that both labelers looked at, 60 unique to labeler 1 (vlad), and 61 unique to labeler 2 (bapt). We could explore this in more detail later if needed. This also meant that I had to create a new unique identifier for the matches, because the unique identifiers from Baptiste’s and Vlad’s files did not match. I constructed the ‘match.id’ from the two file names, the two recording start times, and the two durations. The following analysis only looks at the matches looked at by both Baptiste and Vlad.
Some basic info
First, let’s get some info on how many calls of each type we have in our ‘matched calls’ dataset. Here is a table of the call types, sorted by how common they are (note becuase this uses both sides of the match, the numbers are essentially duplicated).
| Var1 | Freq |
|---|---|
| s | 3201 |
| cc | 1003 |
| chat | 459 |
| agg | 360 |
| soc | 329 |
| al | 160 |
| cc+agg | 59 |
| ukn | 31 |
| s+soc | 27 |
| s+s | 26 |
| mov+s | 22 |
| s+cc | 22 |
| cc+soc | 17 |
| mov | 17 |
| x | 16 |
| mo | 15 |
| mo+s | 13 |
| s+mo | 13 |
| alarm | 9 |
| ld | 8 |
| mo+ld | 8 |
| s+mov | 5 |
| soc+agg | 5 |
| unk | 5 |
| al? | 4 |
| cc+ | 4 |
| s+al | 4 |
| s* | 3 |
| s+c | 3 |
| soc+s | 3 |
| beep | 2 |
| cc+ld | 2 |
| cc+s | 2 |
| ld+cc | 2 |
| ld+mo | 2 |
| mov+cc | 2 |
| mov+ld | 2 |
| s+ld | 2 |
| sc | 2 |
| sn | 2 |
| soc* | 2 |
| soc+cc | 2 |
| soc+mo | 2 |
| # | 1 |
| agg+soc | 1 |
| eating | 1 |
| f | 1 |
| Marker | 1 |
| s+alarm | 1 |
| seq | 1 |
Agreement
Let’s look at the overall level of agreement between Baptiste and Vlad on whether two calls were the same or not. We’ll use an “agreement matrix” to quantify this. Rows represent Baptiste’s label and columns given Vlad’s label. The possible labels are unknown, yes, no, and these are row/column 1, 2, and 3 respectively.
Agreement about who the focal is
Now let’s look at only the matches where both labelers agreed that the call was the same (i.e. answered ‘yes’). Did they agree on who the caller was (individual 1 or 2)? First, let’s just see how many calls we are talking about, and what calls they are.
| Var1 | Freq |
|---|---|
| s | 527 |
| soc | 144 |
| cc | 72 |
| agg | 52 |
| chat | 37 |
| s+soc | 13 |
| ukn | 12 |
| cc+agg | 10 |
| al | 5 |
| cc+soc | 5 |
| mo+s | 3 |
| s+mo | 3 |
| s+s | 3 |
| sc | 2 |
| soc+mo | 2 |
| agg+soc | 1 |
| ld | 1 |
| mov | 1 |
| s* | 1 |
| s+al | 1 |
| s+alarm | 1 |
| s+c | 1 |
| s+cc | 1 |
| sn | 1 |
| soc+agg | 1 |
| soc+cc | 1 |
| soc+s | 1 |
Now let’s look at the agreement in the same way as before. We’ll ignore a few unknowns and mistypings in Baptiste’s labels (there were only a couple of them).
The two labelers agree about the focal individual 87.4 % of the time
Agreement on focal by call type
## Warning in grep("cc", compare.yeses$type.a) | grep("cc", compare.yeses$type.b):
## longer object length is not a multiple of shorter object length
When it comes to close calls in particular (broadly defined), the labelers agree 87 % of the time.
How far apart (in time) are the calls labeled as the same call?
As a check of both our accuracy in synching, and whether the calls labeled as “the same” are likely to actually be the same, let’s have a look at how far apart the calls meant to be “the same” are in time. Here is a histogram of the time differences (from the synched GPS times) between calls that have been identified as “the same”e
The onsets for the vast majority of calls are less then 50 ms apart. Very promising! For comparison, here is the histogram for calls where both labelers agreed they were NOT the same.
We can also get a sense of how accurate our labelers are in measuring the duration of calls (though this will likely be an underestimate because calls that actually originate from a meerkat who is not wearing the collar might be harder to measure accurately). Here is a histogram of the differences in estiamted duration (in msec) from calls that were on two recordings and identified as the same call. I’ve plotted them vs. the average duration between the two labeled calls, since probably this also plays a role.
Looks like we are broadly accurate within about 20 msec, most of the time. As expected, we are more accurate on shorter calls.
Distance apart
If we are picking up something real, we’d expect that the calls identified as the same should come from meerkats that are nearby to one another. Is this true? Let’s look at the distribution of distance apart of the two meerkats for calls identified as the same. 
We’ll also compare to the distances of the ones where calls were not identified as the same.
Looks like the shorter distances are over-represented in the first plot (where calls were the same). Makes sense. Let’s see how much the shorter distances are over-represented there.
The misidentified focal calls more often come form meerkats that are less than ~3m apart. These distances are over-represented amongst the instances where the calls are the same. Distances above ~3m are underrepresented, and this underrepresentation increases with distance. This pattern seems about as expected.
Discrepancy between files used by Vlad and Baptiste
Earlier on, I noted that the match tables used by Vlad and Baptiste were not quite the same. This indicates that a few of the calls must be different between those analyzed by Vlad and those by Baptiste, probably because they were corrected in label files in the meantime. Let’s have a closer look at this by comparing the call tables from Baptiste and Vlad.
First off, let’s check if all the calls are unique within a given table. It turns out there are a few duplicates, though interestingly the acoustic measurements are not necessarily the same. Would be worth looking into these. The table of duplicates from Baptiste’s file (the latest one) is below.
| entryName | t0File | duration | date | t0_idx_dayTimeline | t0GPS_UTC | tEndGPS_UTC | tMidGPS_UTC | ind | fileName | labeller | verifier | callID | callType | isCall | nonFocal | hybrid | noisy | unsureType | unsureFocal | rms | peak.freq.meanentire. | fundamental.meanentire. | max.freq.meanentire. | entropy.meanentire. | hnr.meanentire. | T_Jitter_abs.nf | T_Jitter_rel.nf | T_Jitter_per.nf | Shimmer_abs.nf | Shimmer_rel.nf | Shimmer_per.nf | T_Jitter_abs.f | T_Jitter_rel.f | T_Jitter_per.f | Shimmer_abs.f | Shimmer_rel.f | Shimmer_per.f | closest_neigh_dist | closest_neigh_id | nbr_neigh_below_5m | id_neigh_below_5m | nbr_neigh_below_10m | id_neigh_below_10m | color | x_emitted | y_emitted | t0num | unique.id | unique.string | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4262 | soc nf $ | 01:17:43.015 | 0.442 | 20190713 | 4284 | 2019-07-13 13:11:22.717 | 2019-07-13 13:11:23.15 | 2019-07-13 13:11:22.938 | VHMF001 | HM_VHMF001_HTB_R20_20190707-20190719_file_7_(2019_07_13-11_44_59)_135944_LL_BA.wav | LL | BA | 20190713_VHMF001_01:17:43.015_0.442_soc nf $ | soc | 1 | 1 | 0 | 0 | 0 | 0 | -49.26 | 620 | 470 | 806 | 0.658 | 18.77 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 1.1827592 | VHMF010 | 2 | VHMF010 VHMM016 | 3 | VHMF010 VHMF015 VHMM016 | 1 | NA | NA | 1563016283 | 4262 | HM_VHMF001_HTB_R20_20190707-20190719_file_7_(2019_07_13-11_44_59)_135944_LL_BA.wav|01:17:43.015|0.442|soc nf $ |
| 9774 | s | 01:53:30.407 | 0.037 | 20190713 | 6315 | 2019-07-13 13:45:14.032 | 2019-07-13 13:45:14.069 | 2019-07-13 13:45:14.050 | VHMF015 | HM_VHMF015_RTTB_R05_20190707-20190719_file_7_(2019_07_13-11_44_59)_135944_HB_BA.wav | HB | BA | 20190713_VHMF015_01:53:30.407_0.037_s | s | 1 | 0 | 0 | 0 | 0 | 0 | -43.87 | 921 | 879 | 1097 | 0.478 | 19.58 | 0.0004150 | 0.3997706 | 0.2376147 | 0.0167516 | 0.0492282 | 0.0291260 | 0.0010261 | 0.6936926 | 0.3439069 | 0.0225377 | 0.0673981 | 0.0452496 | 0.7817032 | VHMM007 | 3 | VHMM007 VHMM008 VHMM016 | 5 | VCVM001 VHMM007 VHMM008 VHMF010 VHMM016 | 4 | NA | NA | 1563018314 | 9774 | HM_VHMF015_RTTB_R05_20190707-20190719_file_7_(2019_07_13-11_44_59)_135944_HB_BA.wav|01:53:30.407|0.037|s |
| 12143 | lc * | 02:32:39.021 | 0.105 | 20190712 | 8412 | 2019-07-12 14:20:11.288 | 2019-07-12 14:20:11.393 | 2019-07-12 14:20:11.340 | VHMF019 | HM_VHMF019_MBTB_R25_20190707-20190719_file_6_(2019_07_12-11_44_59)_125944_FG_BA.wav | FG | BA | 20190712_VHMF019_02:32:39.021_0.105_lc * | lc | 1 | 0 | 0 | 0 | 0 | 1 | -37.99 | 854 | 854 | 1015 | 0.363 | 26.58 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 0 | NA | 0 | NA | 0 | NA | NA | 1562934011 | 12143 | HM_VHMF019_MBTB_R25_20190707-20190719_file_6_(2019_07_12-11_44_59)_125944_FG_BA.wav|02:32:39.021|0.105|lc * |
| 14985 | s nf | 01:26:06.579 | 0.047 | 20190716 | 4746 | 2019-07-16 13:19:05.081 | 2019-07-16 13:19:05.128 | 2019-07-16 13:19:05.104 | VHMM007 | HM_VHMM007_LSLT_R17_20190707-20190719_file_10_(2019_07_16-11_44_59)_165944_HB_VD.wav | HB | VD | 20190716_VHMM007_01:26:06.579_0.047_s nf | s | 1 | 1 | 0 | 0 | 0 | 0 | -27.45 | 958 | 958 | 1140 | 0.317 | 24.26 | 0.0002526 | 0.4042105 | 0.2610526 | 0.0194996 | 0.0596105 | 0.0252169 | 0.0002733 | 0.3870206 | 0.2076696 | 0.0197947 | 0.0594217 | 0.0355779 | 1.7722934 | VHMM023 | 2 | VHMM014 VHMM023 | 3 | VHMM014 VHMF015 VHMM023 | 4 | NA | NA | 1563275945 | 14985 | HM_VHMM007_LSLT_R17_20190707-20190719_file_10_(2019_07_16-11_44_59)_165944_HB_VD.wav|01:26:06.579|0.047|s nf |
| 15116 | cc nf | 01:41:52.183 | 0.088 | 20190716 | 5690 | 2019-07-16 13:34:49.072 | 2019-07-16 13:34:49.161 | 2019-07-16 13:34:49.117 | VHMM007 | HM_VHMM007_LSLT_R17_20190707-20190719_file_10_(2019_07_16-11_44_59)_165944_HB_VD.wav | HB | VD | 20190716_VHMM007_01:41:52.183_0.088_cc nf | cc | 1 | 1 | 0 | 0 | 0 | 0 | -48.60 | 554 | 477 | 748 | 0.683 | 22.87 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 3.1696126 | VHMM023 | 1 | VHMM023 | 1 | VHMM023 | 2 | NA | NA | 1563276889 | 15116 | HM_VHMM007_LSLT_R17_20190707-20190719_file_10_(2019_07_16-11_44_59)_165944_HB_VD.wav|01:41:52.183|0.088|cc nf |
| 15118 | cc nf | 01:41:52.400 | 0.082 | 20190716 | 5690 | 2019-07-16 13:34:49.28 | 2019-07-16 13:34:49.371 | 2019-07-16 13:34:49.330 | VHMM007 | HM_VHMM007_LSLT_R17_20190707-20190719_file_10_(2019_07_16-11_44_59)_165944_HB_VD.wav | HB | VD | 20190716_VHMM007_01:41:52.400_0.082_cc nf | cc | 1 | 1 | 0 | 0 | 0 | 0 | -28.69 | 697 | 401 | 888 | 0.788 | 22.40 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 3.1696126 | VHMM023 | 1 | VHMM023 | 1 | VHMM023 | 2 | NA | NA | 1563276889 | 15118 | HM_VHMM007_LSLT_R17_20190707-20190719_file_10_(2019_07_16-11_44_59)_165944_HB_VD.wav|01:41:52.400|0.082|cc nf |
| 15396 | cc | 02:12:42.739 | 0.117 | 20190712 | 7337 | 2019-07-12 14:02:16.21 | 2019-07-12 14:02:16.327 | 2019-07-12 14:02:16.268 | VHMM007 | HM_VHMM007_LSLT_R17_20190707-20190719_file_6_(2019_07_12-11_44_59)_125944_FG_BA.wav | FG | BA | 20190712_VHMM007_02:12:42.739_0.117_cc | cc | 1 | 0 | 0 | 0 | 0 | 0 | -28.61 | 821 | 585 | 987 | 0.576 | 21.21 | 0.0020341 | 1.1934041 | 0.7893801 | 0.0266368 | 0.0795459 | 0.0455189 | 0.0018522 | 1.1364514 | 0.7571896 | 0.0131180 | 0.0400213 | 0.0166616 | 3.5842262 | VCVM001 | 1 | VCVM001 | 2 | VCVM001 VHMM008 | 2 | NA | NA | 1562932936 | 15396 | HM_VHMM007_LSLT_R17_20190707-20190719_file_6_(2019_07_12-11_44_59)_125944_FG_BA.wav|02:12:42.739|0.117|cc |
| 25590 | fu ld+cc | 01:05:56.178 | 0.163 | 20190718 | 3843 | 2019-07-18 13:04:02.206 | 2019-07-18 13:04:02.369 | 2019-07-18 13:04:02.287 | VCVM001 | HM_VCVM001_SOUNDFOC_20190718_BA.WAV | BA | NA | 20190718_VCVM001_01:05:56.178_0.163_fu ld+cc | ld+cc | 1 | 0 | 1 | 0 | 0 | 0 | -28.07 | 711 | 608 | 1644 | 0.205 | 33.15 | 0.0005814 | 0.6462758 | 0.4023493 | 0.0480980 | 0.1421180 | 0.0815341 | 0.0004047 | 0.3674956 | 0.2364139 | 0.0125498 | 0.0378620 | 0.0208409 | 10.5517174 | VHMF022 | 0 | NA | 0 | NA | 3 | NA | NA | 1563447842 | 25590 | HM_VCVM001_SOUNDFOC_20190718_BA.WAV|01:05:56.178|0.163|fu ld+cc |
| 25598 | fu cc+ld | 01:06:27.769 | 0.192 | 20190718 | 3875 | 2019-07-18 13:04:33.796 | 2019-07-18 13:04:33.987 | 2019-07-18 13:04:33.891 | VCVM001 | HM_VCVM001_SOUNDFOC_20190718_BA.WAV | BA | NA | 20190718_VCVM001_01:06:27.769_0.192_fu cc+ld | cc+ld | 1 | 0 | 1 | 0 | 0 | 0 | -32.56 | 812 | 522 | 1431 | 0.215 | 34.69 | 0.0009725 | 0.8299825 | 0.4986836 | 0.0481395 | 0.1425733 | 0.0841951 | 0.0006431 | 0.5131342 | 0.3306223 | 0.0129626 | 0.0390188 | 0.0234304 | 20.6973993 | VHMF022 | 0 | NA | 0 | NA | 3 | NA | NA | 1563447874 | 25598 | HM_VCVM001_SOUNDFOC_20190718_BA.WAV|01:06:27.769|0.192|fu cc+ld |
Now, on to the matter of the calls which are not shared between Baptiste’s and Vlad’s versions of the call table. Let’s first get these.
Turns out the differences stem from the following files:
## [1] "HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav"
## [2] "HM_VHMM007_LSLT_R17_20190707-20190719_file_13_(2019_07_19-11_44_59)_195944_FG_VD.wav"
## [3] "HM_VHMM023_MBLS_R02_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav"## [1] "HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav"
## [2] "HM_VHMM007_LSLT_R17_20190707-20190719_file_13_(2019_07_19-11_44_59)_195944_FG_VD.wav"
## [3] "HM_VHMM023_MBLS_R02_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav"This means that any results from intersections with those files need to be redone by the first labeler (Vlad)! But the rest should be fine.
The match.ids in Baptiste’s matches that need to be also labeled by Vlad are the following:
| x |
|---|
| HM_VHMF010_SOUNDFOC_20190713_BA.WAV|HM_VHMM017_RSTB_R23_20190708-20190720_file_7_(2019_07_13-11_44_59)_135944_LL_VD.wav|01:59:09.237|02:05:43.127|0.177|0.093 |
| HM_VCVM001_SOUNDFOC_20190718_BA.WAV|HM_VHMM016_LTTB_R29_20190707-20190719_file_12_(2019_07_18-11_44_59)_185944_HB_VD.wav|01:51:54.110|01:55:57.957|0.207|0.134 |
| HM_VCVM001_SOUNDFOC_20190719_2_BA.WAV|HM_VHMM007_LSLT_R17_20190707-20190719_file_13_(2019_07_19-11_44_59)_195944_FG_VD.wav|00:22:43.076|02:03:07.621|0.15|0.214 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMM023_MBLS_R02_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:40:18.588|01:49:35.816|0.121|0.192 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMM023_MBLS_R02_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:40:55.451|01:50:12.465|0.148|0.142 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:43:21.275|01:47:31.375|0.121|0.102 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:46:03.887|01:50:14.166|0.148|0.097 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:46:28.987|01:50:38.858|0.155|0.086 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:50:10.546|01:54:20.888|0.157|0.112 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:50:43.731|01:54:54.225|0.177|0.117 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:51:39.001|01:55:49.629|0.126|0.115 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:51:49.844|01:56:00.417|0.093|0.093 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:53:03.480|01:57:14.401|0.122|0.078 |
| HM_VCVM001_SOUNDFOC_20190717_BA.WAV|HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)_175944_FG_VD.wav|01:53:53.518|01:58:04.503|0.105|0.084 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:21:44.897|01:26:53.432|0.121|0.071 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:24:55.450|01:30:03.515|0.093|0.183 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:25:54.827|01:31:02.957|0.128|0.144 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMF022_MBRS_R22_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_LL_VD.wav|01:40:26.288|01:45:58.375|0.099|0.068 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMF022_MBRS_R22_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_LL_VD.wav|01:43:44.880|01:49:16.535|0.086|0.139 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMM014_LSTB_R19_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_BE_VD.wav|01:47:41.471|01:53:14.519|0.104|0.126 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMM014_LSTB_R19_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_BE_VD.wav|01:47:44.128|01:53:17.182|0.086|0.162 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMF022_MBRS_R22_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_LL_VD.wav|01:49:03.861|01:54:35.790|0.086|0.081 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMF022_MBRS_R22_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_LL_VD.wav|01:49:07.198|01:54:38.762|0.082|0.142 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMF022_MBRS_R22_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_LL_VD.wav|01:50:44.975|01:56:16.890|0.099|0.155 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMF022_MBRS_R22_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_LL_VD.wav|01:50:45.791|01:56:17.432|0.108|0.11 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMM007_LSLT_R17_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_LL_VD.wav|01:54:00.169|01:58:54.771|0.034|0.08 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMM014_LSTB_R19_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_BE_VD.wav|01:54:54.225|02:00:27.834|0.117|0.115 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_FG_VD.wav|HM_VHMM014_LSTB_R19_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_BE_VD.wav|01:55:06.884|02:00:40.195|0.089|0.143 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_HB_VD.wav|HM_VHMM007_LSLT_R17_20190707-20190719_file_13(2019_07_19-11_44_59)_195944_FG_VD.wav|01:52:29.298|01:58:16.326|0.101|0.134 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_HB_VD.wav|HM_VHMM007_LSLT_R17_20190707-20190719_file_13(2019_07_19-11_44_59)_195944_FG_VD.wav|01:58:21.827|02:04:08.684|0.104|0.132 |
| HM_VHMF001_HTB_R20_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_HB_VD.wav|HM_VHMM007_LSLT_R17_20190707-20190719_file_13(2019_07_19-11_44_59)_195944_FG_VD.wav|01:58:47.886|02:04:34.619|0.113|0.124 |
| HM_VHMF022_MBRS_R22_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_HB_VD.wav|HM_VHMM007_LSLT_R17_20190707-20190719_file_13(2019_07_19-11_44_59)_195944_FG_VD.wav|02:05:23.249|02:04:37.806|0.094|0.126 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:41:10.644|01:41:24.430|0.103|0.151 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:45:00.360|01:45:13.973|0.124|0.112 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:45:10.984|01:45:24.391|0.11|0.117 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:45:17.380|01:45:30.888|0.114|0.153 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:49:24.920|01:49:38.234|0.127|0.16 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:50:51.641|01:51:04.720|0.12|0.144 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_FG_VD.wav|HM_VHMM017_RSTB_R23_20190708-20190720_file_13(2019_07_19-11_44_59)_195944_LL_VD.wav|02:00:17.047|01:59:51.256|0.121|0.169 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_FG_VD.wav|HM_VHMM014_LSTB_R19_20190707-20190719_file_13(2019_07_19-11_44_59)_195944_FG_VD.wav|02:02:22.259|02:03:08.048|0.129|0.151 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_FG_VD.wav|HM_VHMM014_LSTB_R19_20190707-20190719_file_13(2019_07_19-11_44_59)_195944_FG_VD.wav|02:03:30.524|02:04:16.724|0.047|0.14 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_FG_VD.wav|HM_VHMM014_LSTB_R19_20190707-20190719_file_13(2019_07_19-11_44_59)_195944_FG_VD.wav|02:03:44.323|02:04:30.073|0.113|0.184 |
| HM_VHMM007_LSLT_R17_20190707-20190719_file_13_(2019_07_19-11_44_59)195944_FG_VD.wav|HM_VHMM017_RSTB_R23_20190708-20190720_file_13(2019_07_19-11_44_59)_195944_LL_VD.wav|02:04:43.726|02:04:17.656|0.132|0.148 |
| HM_VHMM008_SHTB_R14_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:59:12.021|01:58:31.665|0.039|0.11 |
| HM_VHMM008_SHTB_R14_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:59:12.021|01:58:31.973|0.039|0.119 |
| HM_VHMM008_SHTB_R14_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:59:12.364|01:58:31.973|0.043|0.119 |
| HM_VHMM008_SHTB_R14_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_LL_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:59:12.364|01:58:32.359|0.043|0.124 |
| HM_VHMM014_LSTB_R19_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:45:52.061|01:45:26.972|0.066|0.13 |
| HM_VHMM014_LSTB_R19_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:46:00.859|01:45:35.465|0.14|0.135 |
| HM_VHMM014_LSTB_R19_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:46:09.200|01:45:44.029|0.176|0.144 |
| HM_VHMM014_LSTB_R19_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:46:45.665|01:46:20.710|0.131|0.172 |
| HM_VHMM014_LSTB_R19_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:50:38.007|01:50:12.465|0.136|0.142 |
| HM_VHMM014_LSTB_R19_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:50:42.047|01:50:16.374|0.171|0.146 |
| HM_VHMM014_LSTB_R19_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:50:45.058|01:50:19.209|0.158|0.124 |
| HM_VHMM014_LSTB_R19_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:51:49.227|01:51:23.318|0.151|0.082 |
| HM_VHMM017_RSTB_R23_20190708-20190720_file_11_(2019_07_17-11_44_59)175944_BE_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:58:41.194|01:59:17.181|0.11|0.112 |
| HM_VHMM021_MBLT_R01_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_HB_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:44:24.660|01:44:41.710|0.03|0.119 |
| HM_VHMM021_MBLT_R01_20190707-20190719_file_11_(2019_07_17-11_44_59)175944_HB_VD.wav|HM_VHMM023_MBLS_R02_20190707-20190719_file_11(2019_07_17-11_44_59)_175944_FG_VD.wav|01:46:07.131|01:46:23.989|0.131|0.052 |
They are all ones associated with those 3 files that were resynched EXCEPT the first 2 (HM_VHMF010_SOUNDFOC_20190713_BA.WAV|HM_VHMM017_RSTB_R23_20190708-20190720_file_7_(2019_07_13-11_44_59)135944_LL_VD.wav|01:59:09.237|02:05:43.127|0.177|0.093 HM_VCVM001_SOUNDFOC_20190718_BA.WAV|HM_VHMM016_LTTB_R29_20190707-20190719_file_12(2019_07_18-11_44_59)_185944_HB_VD.wav|01:51:54.110|01:55:57.957|0.207|0.134)
I am still quite mystified by this, since the corresponding calls are actually present in both calls tables from the two files, so I don’t see why they were matched in Baptiste’s but not in Vlad’s version! But anyway, these 2 should also be labeled by Vlad as well.
Comparing amplitude to neighboring calls
One way to potentially identify focal vs non-focal calls is to compare the amplitude on the 2 devices. However, is this a reliable way to do things? Let’s start by looking at all the calls in a given file of a given type, and computing the amplitude of ones labeled “focal” and “non-focal”. Are they distinguishable? Let’s use the calls2 table (Baptiste’s later one) for this, because it should be more up to date.
The plots below show (for each file) the distribution of RMS (amplitude, high-pass filtered; 100 Hz Butterworth) across the calls labeled as CC’s (broadly defined, accessed via grepping for ‘cc’). In blue, the calls labeled “focal” and in red, the calls labeled “nonfocal” by the labeler (black = distribution over all calls in that category). Note that data are only included for files with > 10 nonfocal and > 10 focal calls. Numbers of each type are shown as text in the plots. Legend background for focal microphone recordings is gray.
Overall, this is not looking promising. Clearly, the labelers are not paying attention to absolute amplitude alone when assessing whether to label something as focal or non-focal, or alternatively our measurement of RMS is not reliable.
One question is whether this could be being confounded by noise. Let’s make the same comparison but for calls labeled “noisy” vs those not labeled “noisy”. Here, we will show the “noisy” calls as blue and the non-noisy as black.
The measured amplitude also does not seem to relate to the “noisy” label.
What about for the calls labeled as focal or nonfocal by Baptiste and Vlad, during the focal/non-focal comparison stage? Did Vlad and Baptiste label these based on their overall amplitude, as measured by our RMS measure?
Since there was high agreement, let’s just use Baptiste’s labels (matches2) for this.
There seems to be some signal there, with the one labeled as focal more likely to be the one with the larger amplitude. However, about 34% of the time the quieter call was labeled as focal.